DC coefficient sign coding scheme

    公开(公告)号:US10194147B2

    公开(公告)日:2019-01-29

    申请号:US15409862

    申请日:2017-01-19

    Applicant: GOOGLE INC.

    Abstract: A sign value of a DC coefficient of a current block is determined using neighbor blocks of the current block. First and second sign values are identified as respectively corresponding to an above neighbor block of the current block and a left neighbor block of the current block. A context value is calculated by applying a first weighting value to the first sign value and a second weighting value to the second sign value. The first weighting value is based on a boundary between the above neighbor block and the current block, and the second weighting value is based on a boundary between the left neighbor block and the current block. A probability value is selected based on the context value. The sign value of the DC coefficient of the current block is then determined using the probability model.

    Transform coefficient coding using level maps

    公开(公告)号:US10244261B2

    公开(公告)日:2019-03-26

    申请号:US15415974

    申请日:2017-01-26

    Applicant: GOOGLE INC.

    Abstract: A method for encoding a transform block in an encoded video bitstream is provided. The method includes encoding a non-zero map indicating positions of the transform block containing non-zero transform coefficients, encoding a respective lower-range level map, and encoding a coefficient residual map. A lower-range level map indicates which values of the non-zero transform coefficients are equal to and which are greater than the map level. Each residual coefficient of the coefficient residual map corresponds to a respective non-zero transform coefficient of the transform block having an absolute value exceeding the maximum map level. An apparatus including a processor and a memory for decoding a transform block is also provided. The memory includes instructions executable by the processor to decode, a non-zero map, decode lower-range level maps up to a maximum map level, and decode a coefficient residual map.

    Context adaptive scan order for entropy coding

    公开(公告)号:US10440394B2

    公开(公告)日:2019-10-08

    申请号:US15259189

    申请日:2016-09-08

    Applicant: GOOGLE INC.

    Abstract: Video coding using a context adaptive scan order for entropy coding may include decoding a current block by identifying a context adaptive scan order for entropy decoding a transform block, which may include identifying non-zero-coefficient probabilities for the transform block such that each location in the transform block corresponds to a respective non-zero-coefficient probability from the non-zero-coefficient probabilities, assigning a respective context adaptive scan order position to each location in the transform block in descending magnitude order of the respective corresponding non-zero-coefficient probabilities such that the context adaptive scan order position for each location exceeds the context adaptive scan order position assigned to entropy coding context locations for the respective location, entropy decoding transform coefficients from the encoded video stream based on the context adaptive scan order, and reconstructing the decoded block based on the transform block.

    Transform Kernel Selection and Entropy Coding

    公开(公告)号:US20180249179A1

    公开(公告)日:2018-08-30

    申请号:US15630071

    申请日:2017-06-22

    Applicant: GOOGLE INC.

    Abstract: Transform kernel candidates including a vertical transform type associated with a vertical motion and a horizontal transform type associated with a horizontal motion can be encoded or decoded. During an encoding operation, a residual block of a current block is transformed according to a selected transform kernel candidate to produce a transform block. A probability model for encoding the selected transform kernel candidate is then identified based on neighbor transform blocks of the transform block. The selected transform kernel candidate is then encoded according to the probability model. During a decoding operation, the encoded transform kernel candidate is decoded using the probability model. The encoded transform block is then decoded by inverse transforming dequantized transform coefficients thereof according to the decoded transform kernel candidate.

    DC COEFFICIENT SIGN CODING SCHEME
    6.
    发明申请

    公开(公告)号:US20180205947A1

    公开(公告)日:2018-07-19

    申请号:US15409862

    申请日:2017-01-19

    Applicant: GOOGLE INC.

    CPC classification number: H04N19/105 H04N19/13 H04N19/167 H04N19/18 H04N19/91

    Abstract: A sign value of a DC coefficient of a current block is determined using neighbor blocks of the current block. First and second sign values are identified as respectively corresponding to an above neighbor block of the current block and a left neighbor block of the current block. A context value is calculated by applying a first weighting value to the first sign value and a second weighting value to the second sign value. The first weighting value is based on a boundary between the above neighbor block and the current block, and the second weighting value is based on a boundary between the left neighbor block and the current block. A probability value is selected based on the context value. The sign value of the DC coefficient of the current block is then determined using the probability model.

    CONTEXT ADAPTIVE SCAN ORDER FOR ENTROPY CODING

    公开(公告)号:US20180070106A1

    公开(公告)日:2018-03-08

    申请号:US15259189

    申请日:2016-09-08

    Applicant: GOOGLE INC.

    Abstract: Video coding using a context adaptive scan order for entropy coding may include decoding a current block by identifying a context adaptive scan order for entropy decoding a transform block, which may include identifying non-zero-coefficient probabilities for the transform block such that each location in the transform block corresponds to a respective non-zero-coefficient probability from the non-zero-coefficient probabilities, assigning a respective context adaptive scan order position to each location in the transform block in descending magnitude order of the respective corresponding non-zero-coefficient probabilities such that the context adaptive scan order position for each location exceeds the context adaptive scan order position assigned to entropy coding context locations for the respective location, entropy decoding transform coefficients from the encoded video stream based on the context adaptive scan order, and reconstructing the decoded block based on the transform block.

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